AutoGluon

Time series forecasting consists in analysing historical signal correlations to anticipate future out- comes . In this work, we focus on probabilistic forecasting in non-stationary contexts, i.e. we aim at producing plausible and diverse predictions where future trajectories can present sharp variations.

Timeseries forecasting in simple words means to forecast or to predict the future value(eg-stock price) over a period of time .

Set up the Python Environment so modeltime. gluonts can connect to the gluonts python package.